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  • Arthur Burkhardt thinks this is interesting:

Nonetheless, no matter how mature a company is, there will always be a need to perform reactive data quality maintenance tasks. Again, it is about data adequacy to a business need, not perfect data. Data correction projects must have clearly established requirements, objectives, and metrics to measure success. Furthermore, every data issue has a root cause. When correcting existing data issues, make sure to identify why and how the issue occurred and implement corrective actions to prevent similar anomalies in the future.


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Research the best way to log analyses, causes, and proposed resolutions